]]>http://www.shujianliu.com/blogs/a-brief-history-of-cnns-in-image-segmentation-from-r-cnn-to-mask-r-cnn/feed/0[D] What are the best recent ML breakthroughs which still don’t have open source implementations? • r/MachineLearninghttp://www.shujianliu.com/blogs/d-what-are-the-best-recent-ml-breakthroughs-which-still-dont-have-open-source-implementations-%e2%80%a2-rmachinelearning/
http://www.shujianliu.com/blogs/d-what-are-the-best-recent-ml-breakthroughs-which-still-dont-have-open-source-implementations-%e2%80%a2-rmachinelearning/#respondWed, 26 Apr 2017 14:27:53 +0000http://www.shujianliu.com/blogs/?p=401

[D] What are the best recent ML breakthroughs which still don’t have open source implementations? • r/MachineLearning

I thought it would be a good idea to maintain a list so that people can take up the challenge.

There are two clear trends in the big-data ecosystem: the growth of machine learning use cases that leverage large distributed data sets, and the growth of Sparkâs Machine Learning libraries (often referred to as MLlib) for these use cases. In fact, Sparkâs MLlib library is arguably the leading solution for machine learning on large distributed data sets. Intel and Cloudera have collaborated to speed up Spark’s ML algorithms, via integration with Intel’s Math Kernel Library (IntelÂ® MKL). Read More

Kaggle Past Competitions

If you are facing a data science problem, there is a good chance that you can find inspiration here! This page could be improved by adding more competitions and more solutions: pull requests are more than welcome. Warning: this is a work in progress, many competitions are missing solutions.